AI for public-sector records without losing control of the record.

adapterOS runs on procurement packets, program files, case materials, and public-records workflows inside the agency boundary, then leaves legal, IT, and program owners with cited work and a replayable review record.

Inside your environmentNo document egress

Reviewer asksWhich renewal terms changed, and what needs legal review?

Workspace answersThree clauses changed. One adds an approval dependency.

Approved sources, cited

MSA v4 sec. 8.2
Addendum p.3
Policy sec. 11

Decision record

Policy: Human approval before use
Record: Kept locally for replay

Discuss a pilot Explore adapterOS

See the review packet

The point is not a better chat box. It is a useful work record a reviewer can inspect after the meeting, audit, or handoff.

The boundary comes first.

Some work should not leave the room, the facility, or the customer network. MLNavigator starts there: local hardware, approved source sets, clear reviewer routes, and records that show what happened.

Customer environment

Source docs

adapterOS

Specialist workspace

Review records

No routine document egress

Start with a real workflow, not a platform pitch.

adapterOS is the first workspace: a place where a team can try AI on one bounded document job, see whether it helps, and keep enough evidence to defend the result.

Local

Keep the work inside.

Pilot deployments are designed around local hardware and no routine egress for sensitive source material.

Scoped

Use the right sources.

Each workspace is configured around a specific document set, policy boundary, and reviewer path.

Inspectable

Leave a record people can read.

Citations, control results, and reviewer notes remain attached to the work they supported.

What the product makes routine.

The research matters only if it changes how the work happens. These are the habits adapterOS is built to make ordinary in a controlled environment.

Offline inferenceRun sensitive workflows on local hardware without making cloud model upload the default path.

MLX/local model pathsResearch and deployment work focuses on practical local model operations, especially where Apple and edge hardware fit.

Approved source setsWorkspaces are bounded by the material, policies, and reviewer routes that define the job.

Policy-gated answersAnswers carry citations, policy results, and the context a human reviewer needs to decide what happens next.

Replay evidenceExecution records, source links, and reviewer notes stay close enough to make the work inspectable later.

Operator reviewThe runtime is designed to support accountable operation, not to hide judgment behind a conversational surface.

A pilot starts with one bounded workflow.

Bring one document job that already matters. We shape the workspace around the people, sources, and review standard that make that job real.

Pick the workflow

Choose the review, reporting, or compliance task where sensitive documents already slow the team down.

Configure the workspace

Load the approved sources, define the reviewer route, and set the boundary for what the specialist can use.

Use it with real work

Run questions, comparisons, summaries, and drafts on local hardware with the team that owns the process.

Decide with evidence

Measure usefulness, source quality, review fit, deployment burden, and whether the workflow should expand.

Pick the conversation you came for.

The same product supports four different relationships. Choose the one that matches why you are here; your domain context travels with you.

Understand the product

NSF I-Corps
ACCEL-KS Grant
50+ operator interviews
Patent pending

Start with one work record your team can inspect.

Bring one sensitive workflow, the source boundary, and the review standard it has to satisfy. We will map the pilot around the record your team needs at the end.

Start discovery See the pilot path

Or see the evidence first →